josephmisiti/awesome-machine-learning
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Joseph Misiti 2015-11-27 10:56:53 -05:00
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@ -645,7 +645,8 @@ on MNIST digits[DEEP LEARNING]
* [Featureforge](https://github.com/machinalis/featureforge) A set of tools for creating and testing machine learning features, with a scikit-learn compatible API * [Featureforge](https://github.com/machinalis/featureforge) A set of tools for creating and testing machine learning features, with a scikit-learn compatible API
* [MLlib in Apache Spark](http://spark.apache.org/docs/latest/mllib-guide.html) - Distributed machine learning library in Spark * [MLlib in Apache Spark](http://spark.apache.org/docs/latest/mllib-guide.html) - Distributed machine learning library in Spark
* [scikit-learn](http://scikit-learn.org/) - A Python module for machine learning built on top of SciPy. * [scikit-learn](http://scikit-learn.org/) - A Python module for machine learning built on top of SciPy.
* [SimpleAI](https://github.com/simpleai-team/simpleai) Python implementation of many of the artificial intelligence algorithms described on the book "Artificial Intelligence, a Modern Approach". It focuses on providing an easy to use, well documented and tested library. * [metric-learn](https://github.com/all-umass/metric-learn) - A Python module for metric learning.
* [SimpleAI](http://github.com/simpleai-team/simpleai) Python implementation of many of the artificial intelligence algorithms described on the book "Artificial Intelligence, a Modern Approach". It focuses on providing an easy to use, well documented and tested library.
* [astroML](http://www.astroml.org/) - Machine Learning and Data Mining for Astronomy. * [astroML](http://www.astroml.org/) - Machine Learning and Data Mining for Astronomy.
* [graphlab-create](http://graphlab.com/products/create/docs/) - A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame. * [graphlab-create](http://graphlab.com/products/create/docs/) - A library with various machine learning models (regression, clustering, recommender systems, graph analytics, etc.) implemented on top of a disk-backed DataFrame.
* [BigML](https://bigml.com) - A library that contacts external servers. * [BigML](https://bigml.com) - A library that contacts external servers.
@ -708,6 +709,7 @@ on MNIST digits[DEEP LEARNING]
* [vincent](https://github.com/wrobstory/vincent) - A Python to Vega translator. * [vincent](https://github.com/wrobstory/vincent) - A Python to Vega translator.
* [d3py](https://github.com/mikedewar/d3py) - A plottling library for Python, based on [D3.js](http://d3js.org/). * [d3py](https://github.com/mikedewar/d3py) - A plottling library for Python, based on [D3.js](http://d3js.org/).
* [ggplot](https://github.com/yhat/ggplot) - Same API as ggplot2 for R. * [ggplot](https://github.com/yhat/ggplot) - Same API as ggplot2 for R.
* [ggfortify](https://github.com/sinhrks/ggfortify) - Unified interface to ggplot2 popular R packages.
* [Kartograph.py](https://github.com/kartograph/kartograph.py) - Rendering beautiful SVG maps in Python. * [Kartograph.py](https://github.com/kartograph/kartograph.py) - Rendering beautiful SVG maps in Python.
* [pygal](http://pygal.org/) - A Python SVG Charts Creator. * [pygal](http://pygal.org/) - A Python SVG Charts Creator.
* [PyQtGraph](https://github.com/pyqtgraph/pyqtgraph) - A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy. * [PyQtGraph](https://github.com/pyqtgraph/pyqtgraph) - A pure-python graphics and GUI library built on PyQt4 / PySide and NumPy.